Esta página se ha traducido con Cloud Translation API.
Switch to English

Traducir contenido

Usa la API de Cloud Translation avanzado

Cuando hayas entrenado correctamente tu modelo, puedes traducir contenido con el método translateText de la API de Cloud Translation Advanced. Esta versión de la API admite glosarios y solicitudes de traducción por lotes.

LÍNEA DE REST Y CMD

Asegúrate de haber habilitado la API de Cloud AutoML para tu proyecto. Esto es necesario cuando se usan modelos de AutoML con la API de AutoML. Consulta la página sobre el documento de introducción para habilitar la API.

Antes de usar cualquiera de los siguientes datos de solicitud, realiza estos reemplazos:

  • project-number-or-id: el número o ID de tu proyecto de Google Cloud

Método HTTP y URL:

POST https://translation.googleapis.com/v3/projects/project-number-or-id/locations/us-central1:translateText

Cuerpo JSON de la solicitud:

{
  "model": "projects/project-number-or-id/locations/us-central1/models/TRL1395675701985363739",
  "sourceLanguageCode": "en",
  "targetLanguageCode": "ru",
  "contents": ["Dr. Watson, please discard your trash. You've shared unsolicited email with me.
  Let's talk about spam and importance ranking in a confidential mode."]
}

Para enviar tu solicitud, elige una de estas opciones:

curl

Guarda el cuerpo de la solicitud en un archivo llamado request.json y ejecuta el siguiente comando:

curl -X POST \
-H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
https://translation.googleapis.com/v3/projects/project-number-or-id/locations/us-central1:translateText

PowerShell

Guarda el cuerpo de la solicitud en un archivo llamado request.json y ejecuta el siguiente comando:

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
  -Method POST `
  -Headers $headers `
  -ContentType: "application/json; charset=utf-8" `
  -InFile request.json `
  -Uri "https://translation.googleapis.com/v3/projects/project-number-or-id/locations/us-central1:translateText
" | Select-Object -Expand Content

Deberías recibir una respuesta JSON similar a la que se muestra a continuación:

{
  "translation": {
    "translatedText": "Доктор Ватсон, пожалуйста, откажитесь от своего мусора.
    Вы поделились нежелательной электронной почтой со мной. Давайте поговорим о
    спаме и важности рейтинга в конфиденциальном режиме.",
    "model": "projects/project-number/locations/us-central1/models/TRL1395675701985363739"
  }
}

Go

import (
	"context"
	"fmt"
	"io"

	translate "cloud.google.com/go/translate/apiv3"
	translatepb "google.golang.org/genproto/googleapis/cloud/translate/v3"
)

// translateTextWithModel translates input text and returns translated text.
func translateTextWithModel(w io.Writer, projectID string, location string, sourceLang string, targetLang string, text string, modelID string) error {
	// projectID := "my-project-id"
	// location := "us-central1"
	// sourceLang := "en"
	// targetLang := "fr"
	// text := "Hello, world!"
	// modelID := "your-model-id"

	ctx := context.Background()
	client, err := translate.NewTranslationClient(ctx)
	if err != nil {
		return fmt.Errorf("NewTranslationClient: %v", err)
	}
	defer client.Close()

	req := &translatepb.TranslateTextRequest{
		Parent:             fmt.Sprintf("projects/%s/locations/%s", projectID, location),
		SourceLanguageCode: sourceLang,
		TargetLanguageCode: targetLang,
		MimeType:           "text/plain", // Mime types: "text/plain", "text/html"
		Contents:           []string{text},
		Model:              fmt.Sprintf("projects/%s/locations/%s/models/%s", projectID, location, modelID),
	}

	resp, err := client.TranslateText(ctx, req)
	if err != nil {
		return fmt.Errorf("TranslateText: %v", err)
	}

	// Display the translation for each input text provided
	for _, translation := range resp.GetTranslations() {
		fmt.Fprintf(w, "Translated text: %v\n", translation.GetTranslatedText())
	}

	return nil
}

Java

import com.google.cloud.translate.v3.LocationName;
import com.google.cloud.translate.v3.TranslateTextRequest;
import com.google.cloud.translate.v3.TranslateTextResponse;
import com.google.cloud.translate.v3.Translation;
import com.google.cloud.translate.v3.TranslationServiceClient;
import java.io.IOException;

public class TranslateTextWithModel {

  public static void translateTextWithModel() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR-PROJECT-ID";
    // Supported Languages: https://cloud.google.com/translate/docs/languages
    String sourceLanguage = "your-source-language";
    String targetLanguage = "your-target-language";
    String text = "your-text";
    String modelId = "YOUR-MODEL-ID";
    translateTextWithModel(projectId, sourceLanguage, targetLanguage, text, modelId);
  }

  // Translating Text with Model
  public static void translateTextWithModel(
      String projectId, String sourceLanguage, String targetLanguage, String text, String modelId)
      throws IOException {

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (TranslationServiceClient client = TranslationServiceClient.create()) {
      // Supported Locations: `global`, [glossary location], or [model location]
      // Glossaries must be hosted in `us-central1`
      // Custom Models must use the same location as your model. (us-central1)
      String location = "us-central1";
      LocationName parent = LocationName.of(projectId, location);
      String modelPath =
          String.format("projects/%s/locations/%s/models/%s", projectId, location, modelId);

      // Supported Mime Types: https://cloud.google.com/translate/docs/supported-formats
      TranslateTextRequest request =
          TranslateTextRequest.newBuilder()
              .setParent(parent.toString())
              .setMimeType("text/plain")
              .setSourceLanguageCode(sourceLanguage)
              .setTargetLanguageCode(targetLanguage)
              .addContents(text)
              .setModel(modelPath)
              .build();

      TranslateTextResponse response = client.translateText(request);

      // Display the translation for each input text provided
      for (Translation translation : response.getTranslationsList()) {
        System.out.printf("Translated text: %s\n", translation.getTranslatedText());
      }
    }
  }
}

Node.js

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'YOUR_PROJECT_ID';
// const location = 'us-central1';
// const modelId = 'YOUR_MODEL_ID';
// const text = 'text to translate';

// Imports the Google Cloud Translation library
const {TranslationServiceClient} = require('@google-cloud/translate');

// Instantiates a client
const translationClient = new TranslationServiceClient();
async function translateTextWithModel() {
  // Construct request
  const request = {
    parent: `projects/${projectId}/locations/${location}`,
    contents: [text],
    mimeType: 'text/plain', // mime types: text/plain, text/html
    sourceLanguageCode: 'en',
    targetLanguageCode: 'ja',
    model: `projects/${projectId}/locations/${location}/models/${modelId}`,
  };

  try {
    // Run request
    const [response] = await translationClient.translateText(request);

    for (const translation of response.translations) {
      console.log(`Translated Content: ${translation.translatedText}`);
    }
  } catch (error) {
    console.error(error.details);
  }
}

translateTextWithModel();

PHP

use Google\Cloud\Translate\V3\TranslationServiceClient;

$translationServiceClient = new TranslationServiceClient();

/** Uncomment and populate these variables in your code */
// $modelId = '[MODEL ID]';
// $text = 'Hello, world!';
// $targetLanguage = 'fr';
// $sourceLanguage = 'en';
// $projectId = '[Google Cloud Project ID]';
// $location = 'global';
$modelPath = sprintf(
    'projects/%s/locations/%s/models/%s',
    $projectId,
    $location,
    $modelId
);
$contents = [$text];
$formattedParent = $translationServiceClient->locationName(
    $projectId,
    $location
);

// Optional. Can be "text/plain" or "text/html".
$mimeType = 'text/plain';

try {
    $response = $translationServiceClient->translateText(
        $contents,
        $targetLanguage,
        $formattedParent,
        [
            'model' => $modelPath,
            'sourceLanguageCode' => $sourceLanguage,
            'mimeType' => $mimeType
        ]
    );
    // Display the translation for each input text provided
    foreach ($response->getTranslations() as $translation) {
        printf('Translated text: %s' . PHP_EOL, $translation->getTranslatedText());
    }
} finally {
    $translationServiceClient->close();
}

Python


from google.cloud import translate

def translate_text_with_model(
    text="YOUR_TEXT_TO_TRANSLATE",
    project_id="YOUR_PROJECT_ID",
    model_id="YOUR_MODEL_ID",
):
    """Translates a given text using Translation custom model."""

    client = translate.TranslationServiceClient()

    location = "us-central1"
    parent = f"projects/{project_id}/locations/{location}"
    model_path = f"{parent}/models/{model_id}"

    # Supported language codes: https://cloud.google.com/translate/docs/languages
    response = client.translate_text(
        request={
            "contents": [text],
            "target_language_code": "ja",
            "model": model_path,
            "source_language_code": "en",
            "parent": parent,
            "mime_type": "text/plain",  # mime types: text/plain, text/html
        }
    )
    # Display the translation for each input text provided
    for translation in response.translations:
        print("Translated text: {}".format(translation.translated_text))

Ruby

require "google/cloud/translate"

# project_id = "[Google Cloud Project ID]"
# location_id = "[LOCATION ID]"
# model_id = "[MODEL ID]"

# The `model` type requested for this translation.
model = "projects/#{project_id}/locations/#{location_id}/models/#{model_id}"
# The content to translate in string format
contents = ["Hello, world!"]
# Required. The BCP-47 language code to use for translation.
target_language = "fr"
# Optional. The BCP-47 language code of the input text.
source_language = "en"
# Optional. Can be "text/plain" or "text/html".
mime_type = "text/plain"

client = Google::Cloud::Translate.translation_service

parent = client.location_path project: project_id, location: location_id

response = client.translate_text parent:               parent,
                                 contents:             contents,
                                 target_language_code: target_language,
                                 source_language_code: source_language,
                                 model:                model,
                                 mime_type:            mime_type

# Display the translation for each input text provided
response.translations.each do |translation|
  puts "Translated text: #{translation.translated_text}"
end

Usa AutoML Translation

También puedes usar AutoML Translation para traducir contenido con modelos personalizados.

IU web

  1. Ve a la página Modelos de AutoML Translation en Google Cloud Console.

  2. Si el modelo que deseas usar se encuentra en otro proyecto, selecciona el proyecto del selector de proyectos en la barra de título.

  3. En la lista de modelos, selecciona el que usarás para traducir texto.

  4. Haz clic en la pestaña Predecir del modelo.

  5. En el cuadro de texto, ingresa el contenido que deseas traducir y haz clic en Traducir.

    Puedes comparar los resultados de tu modelo personalizado con el modelo base (modelo de NMT de Google), que Cloud Translation avanzado usa de forma predeterminada.

LÍNEA DE REST Y CMD

Antes de usar cualquiera de los datos de solicitud a continuación, realiza los siguientes reemplazos:

  • model-name: el nombre completo de tu modelo. Incluye el nombre y la ubicación del proyecto. El nombre de un modelo es similar al siguiente ejemplo: projects/project-id/locations/us-central1/models/model-id.
  • source-language-text: es el texto que deseas traducir desde el idioma de origen al idioma de destino.

Método HTTP y URL:

POST https://automl.googleapis.com/v1/model-name:predict

Cuerpo JSON de la solicitud:

{
  "payload" : {
     "textSnippet": {
        "content": "source-language-text"
      }
  }
}

Para enviar tu solicitud, elige una de estas opciones:

curl

Guarda el cuerpo de la solicitud en un archivo llamado request.json y ejecuta el siguiente comando:

curl -X POST \
-H "Authorization: Bearer "$(gcloud auth application-default print-access-token) \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
https://automl.googleapis.com/v1/model-name:predict

PowerShell

Guarda el cuerpo de la solicitud en un archivo llamado request.json y ejecuta el siguiente comando:

$cred = gcloud auth application-default print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
  -Method POST `
  -Headers $headers `
  -ContentType: "application/json; charset=utf-8" `
  -InFile request.json `
  -Uri "https://automl.googleapis.com/v1/model-name:predict" | Select-Object -Expand Content

Deberías recibir una respuesta JSON similar a la que se muestra a continuación:

{
  "payload": [
    {
      "translation": {
        "translatedContent": {
          "content": "target-language-text"
        }
      }
    }
  ]
}

Go

import (
	"context"
	"fmt"
	"io"

	automl "cloud.google.com/go/automl/apiv1"
	automlpb "google.golang.org/genproto/googleapis/cloud/automl/v1"
)

// translatePredict does a prediction for translate.
func translatePredict(w io.Writer, projectID string, location string, modelID string, content string) error {
	// projectID := "my-project-id"
	// location := "us-central1"
	// modelID := "TRL123456789..."
	// content := "text to translate"

	ctx := context.Background()
	client, err := automl.NewPredictionClient(ctx)
	if err != nil {
		return fmt.Errorf("NewPredictionClient: %v", err)
	}
	defer client.Close()

	req := &automlpb.PredictRequest{
		Name: fmt.Sprintf("projects/%s/locations/%s/models/%s", projectID, location, modelID),
		Payload: &automlpb.ExamplePayload{
			Payload: &automlpb.ExamplePayload_TextSnippet{
				TextSnippet: &automlpb.TextSnippet{
					Content:  content,
					MimeType: "text/plain", // Types: "text/plain", "text/html"
				},
			},
		},
	}

	resp, err := client.Predict(ctx, req)
	if err != nil {
		return fmt.Errorf("Predict: %v", err)
	}

	for _, payload := range resp.GetPayload() {
		fmt.Fprintf(w, "Translated content: %v\n", payload.GetTranslation().GetTranslatedContent().GetContent())
	}

	return nil
}

Java

import com.google.cloud.automl.v1.ExamplePayload;
import com.google.cloud.automl.v1.ModelName;
import com.google.cloud.automl.v1.PredictRequest;
import com.google.cloud.automl.v1.PredictResponse;
import com.google.cloud.automl.v1.PredictionServiceClient;
import com.google.cloud.automl.v1.TextSnippet;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Paths;

class TranslatePredict {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR_PROJECT_ID";
    String modelId = "YOUR_MODEL_ID";
    String filePath = "path_to_local_file.txt";
    predict(projectId, modelId, filePath);
  }

  static void predict(String projectId, String modelId, String filePath) throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PredictionServiceClient client = PredictionServiceClient.create()) {
      // Get the full path of the model.
      ModelName name = ModelName.of(projectId, "us-central1", modelId);

      String content = new String(Files.readAllBytes(Paths.get(filePath)));

      TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).build();
      ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
      PredictRequest predictRequest =
          PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();

      PredictResponse response = client.predict(predictRequest);
      TextSnippet translatedContent =
          response.getPayload(0).getTranslation().getTranslatedContent();
      System.out.format("Translated Content: %s\n", translatedContent.getContent());
    }
  }
}

Node.js

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const projectId = 'YOUR_PROJECT_ID';
// const location = 'us-central1';
// const modelId = 'YOUR_MODEL_ID';
// const filePath = 'path_to_local_file.txt';

// Imports the Google Cloud AutoML library
const {PredictionServiceClient} = require('@google-cloud/automl').v1;
const fs = require('fs');

// Instantiates a client
const client = new PredictionServiceClient();

// Read the file content for translation.
const content = fs.readFileSync(filePath, 'utf8');

async function predict() {
  // Construct request
  const request = {
    name: client.modelPath(projectId, location, modelId),
    payload: {
      textSnippet: {
        content: content,
      },
    },
  };

  const [response] = await client.predict(request);

  console.log(
    'Translated content: ',
    response.payload[0].translation.translatedContent.content
  );
}

predict();

PHP

use Google\Cloud\AutoMl\V1\ExamplePayload;
use Google\Cloud\AutoMl\V1\PredictionServiceClient;
use Google\Cloud\AutoMl\V1\TextSnippet;

/** Uncomment and populate these variables in your code */
// $projectId = '[Google Cloud Project ID]';
// $location = 'us-central1';
// $modelId = 'my_model_id_123';
// $content = 'text to predict';

$client = new PredictionServiceClient();

try {
    // get full path of model
    $formattedName = $client->modelName(
        $projectId,
        $location,
        $modelId);

    // create payload
    $textSnippet = (new TextSnippet())
        ->setContent($content);
    $payload = (new ExamplePayload())
        ->setTextSnippet($textSnippet);

    // predict with above model and payload
    $response = $client->predict($formattedName, $payload);
    $annotations = $response->getPayload();

    // display results
    foreach ($annotations as $annotation) {
        $translatedContent = $annotation->getTranslation()
            ->getTranslatedContent();
        printf('Translated content: %s' . PHP_EOL, $translatedContent->getContent());
    }
} finally {
    $client->close();
}

Python

Antes de que puedas ejecutar este ejemplo de código, debes instalar las bibliotecas cliente de Python.

  • El parámetro model_full_id es el nombre completo de tu modelo. Por ejemplo: projects/434039606874/locations/us-central1/models/3745331181667467569
from google.cloud import automl

# TODO(developer): Uncomment and set the following variables
# project_id = "YOUR_PROJECT_ID"
# model_id = "YOUR_MODEL_ID"
# file_path = "path_to_local_file.txt"

prediction_client = automl.PredictionServiceClient()

# Get the full path of the model.
model_full_id = automl.AutoMlClient.model_path(
    project_id, "us-central1", model_id
)

# Read the file content for translation.
with open(file_path, "rb") as content_file:
    content = content_file.read()
content.decode("utf-8")

text_snippet = automl.TextSnippet(content=content)
payload = automl.ExamplePayload(text_snippet=text_snippet)

response = prediction_client.predict(name=model_full_id, payload=payload)
translated_content = response.payload[0].translation.translated_content

print(u"Translated content: {}".format(translated_content.content))